Index
Electronic HRM in the Smart Era
ISBN: 978-1-78714-316-6, eISBN: 978-1-78714-315-9
Publication date: 9 August 2017
This content is currently only available as a PDF
Citation
(2017), "Index", Bondarouk, T., Ruël, H.J.M. and Parry, E. (Ed.) Electronic HRM in the Smart Era (The Changing Context of Managing People), Emerald Publishing Limited, Leeds, pp. 339-353. https://doi.org/10.1108/978-1-78714-315-920161014
Publisher
:Emerald Publishing Limited
Copyright © 2017 Emerald Publishing Limited
INDEX
Ability-motivation-opportunity framework (AMO framework)
, 147
Access to Capital
, 16, 18, 22, 25
Activity dimension
, 36
‘Administrative/operational’ theory
, 325, 333–334
Adopter/abandonment system dynamic model
, 81
Agent dimension
, 36
‘Agential humanist’ position
, 267, 270, 271, 274, 276
Agential realism
, 270, 274
Alignment
, 142
Alternative research model test
, 160–162
Ambiguity
, 64
American Society for Personal Administration (ASPA)
, 63
AMO framework. See Ability-motivation-opportunity framework (AMO framework)
Amris
, 42, 43
“Analyzers”
, 146
Anticipated Organizational Growth
, 13, 14, 18, 25
Architectural competence
, 141
ASPA. See American Society for Personal Administration (ASPA)
Augmentation
, 225, 227
Australia, IS issues in
, 207–208
Australian organisations, e-HRM challenges in
, 202, 208, 211, 215, 217
Automational e-HRM systems
, 89
Average variance extracted (AVE)
, 155
Barclays
, 70
BBC instrument
, 332
Big data
, 62, 80, 101, 222
Business areas (BAs)
, 185, 197
Business relationships (BR)
, 206, 213
Capability Builder
, 325
Capability configuration
, 140, 151, 158, 160
analysis
, 166
SHRM and e-HRM
, 164
CedarCrestone HR Systems surveys
, 72, 82
Channels
, 66
Click-Call-Face customers
, 324
Client interface
, 36
Cloud-based
HR software
, 17–18
HRIS adoption model
, 24, 25
Cluster analysis
, 143, 152
Code of conduct
, 177, 299
Compatibility
, 7, 9, 18, 35, 216, 217
of business processes
, 12
of SMEs’ e-HRM technology
, 163
Component capabilities
, 141
Component competence
, 141
Conceptualisation of e-HRM
, 263, 267, 272
Configurational approach
, 160, 162, 251–252, 264
Constructive ethnographic research
, 276–277
Content analysis
, 184–185
Continuous professional development (CPD)
, 301
Controlled vocabularies
, 73
“CORE”
, 184, 186
role in supporting business strategy
, 193
strategic potential
, 192–193
Corporate strategic development
, 317–318, 326
Cost
efficiency improvement
, 187
reductions
, 177
Covariance-based techniques
, 154, 158
CPD. See Continuous professional development (CPD)
Cultural values
, 92, 176, 181
Customers
, 93, 99, 298
Click-Call-Face
, 324
for higher service quality
, 34
internal
, 203
service and efficiency improvement
, 187–188
Cyber-vetting
, 291, 294–295
D&M model. See DeLone and McLean model (D&M model)
Data analytic software
, 64n1
Data collection
, 148
descriptive statistics of
research variables
, 149
strategic HRM and e-HRM capabilities
, 150
HRD
, 148
Data governance programs
, 101–103
Data mining process
, 64, 294, 295
Data quality
, 95–97, 104, 105
issues
, 94
poor
, 102
recommendations
, 101–103
Data-driven business
, 323
Decision support systems perspective (DSS perspective)
, 97, 208
“Defenders”
, 146
DeLone and McLean model (D&M model)
, 92–96
integration into e-HRM
, 99–101
quality components
, 101
Descriptive analytics
, 63
Design mode
, 269
d-HRM. See Digital HRM (d-HRM)
Diffusion of innovation theory (DOI theory)
, 61, 62, 66, 67, 79–80
Diffusion process
, 62, 67, 68
Digital HRM (d-HRM)
, 35
Digital systems
, 312, 323, 326
Digital technologies
, 38, 315, 325, 335
Digitization model
, 46
Digitization on HRM profession
activities of HRM professional
, 334–335
automation risk role analysis
, 320
corporate strategy development
, 318
digital systems and robots
, 312
economic and social effects of
, 313
effects of
, 335–336
findings/results
, 322
secondary analysis HRM practice monitor
, 325–328, 331
sessions with HRM professionals
, 323–325
future work skills
, 316, 317
HRM roles
, 315
labels of HRM department
, 335
limitations of HRM practice monitor
, 330–334
primary role of HRM professional
, 334
research design
, 319
HRM professionals
, 319–321
secondary analysis HRM practice monitor
, 321–322
theoretical background
, 314
See also Electronic-HRM (e-HRM)
Direct effects model
, 160
DOI theory. See Diffusion of innovation theory (DOI theory)
Doomsday scenario
, 224
DSS perspective. See Decision support systems perspective (DSS perspective)
Economic and social effects of digitization
, 313
EDI adoption model
, 9, 23
Effective data governance
, 105
Effective training
, 101, 299
e-HRM. See Electronic human resource management (e-HRM)
Electronic human resource management (e-HRM)
, 5, 36–37, 88, 138, 139, 154, 175, 202, 262, 315
impact
, 178–179
Australian organisations
, 202–203
challenges
, 202, 211
consequences
, 178
descriptive statistics
, 150
development issues
, 214–215
discussion
, 98
data quality recommendations
, 101–103
future research
, 104–105
integrating D&M model into e-HRM
, 99–101
limitations
, 105
system quality recommendations
, 103–104
HR issues
, 212–214
implications, limitations and suggestions for future research
, 215–217
interview questions
, 108
limitations
, 279–280
literature review
, 203
e-HRM and outcomes
, 203–204
e-HRM literature on system success
, 91–92
information systems managerial issues reported in IT literature
, 204–207
IS issues in Australia
, 207–208
IS success model
, 92–94
methods
, 94–95, 208
considerations
, 276–278
perspectives on e-HRM
, 208–209
semi-structured interview questions
, 210
motives for e-HRM adoption
, 194
as nexus of practices and material arrangements
, 272–276
organizational capabilities
, 141–142
and outcomes
, 203–204
project
, 89–91
research
, 263
future
, 278–279
theories in
, 264–267
results
, 95
data quality
, 95–97
service quality
, 98
system quality
, 97–98
sociomateriality in information systems research
, 267–272
systems
, 88
technical challenges
, 211–212
See also Digitization on HRM profession; Strategic human resource management (SHRM)
Employee self-service
, 7, 19, 23, 83, 324, 334
Employer
, 120, 288, 294
branding
, 43, 45, 111, 115, 118, 292–293
Employment debate
, 223–226, 245
Enterprise resource planning system (ERP system)
, 35, 103–104, 263–264, 268–269
Environmental context
, 9, 14–16
Environmental factors
, 2, 8, 9, 24, 92
EQS, Covariance-based techniques
, 154
E-recruitment
, 111
experience with
, 120
perceived fairness
, 120
Web 2.0
, 129–130
ERP system. See Enterprise resource planning system (ERP system)
Ethical guidelines
, 289–290, 299
Ethnographic sensibility
, 276
Evidence-based approach
, 64
Experimenters
, 81
Facebook
, 43–44, 111–112, 117, 123–124
FinCO company
, 184, 185, 189, 193
business areas
, 197
HR in
, 186
HR professionals and line managers in
, 194
Firm
e-HRM organizational capabilities
, 147
systems capabilities
, 141
“Fit as covariation”
, 143
“Fit as gestalts”
, 143
“Fit as matching”
, 143
“Fit as mediation”
, 143
“Fit as moderation”
, 143
“Fit as profile deviation”
, 143
Formal recruitment procedures
, 110–111
Gamification
, 38, 39, 249, 250
“Gestalts” perspective
, 143, 144
See also Manufacturing SMEs
Glassdoor (websites)
, 292, 293
Global orientation improvement
, 187, 194
Google
N-Gram charts
, 72
Project Oxygen
, 69–70
Gravitate
, 42, 43
Growth need strength (GNS)
, 228, 244
Harvard Business Review
, 75
Headquarters (HQ)
, 40
Hermeneutical method
, 277
High-performance work systems (HPWS)
, 142
Homogeneity test
, 319
Hospitality industry
, 34, 37–38
Hotels
, 34, 36
HPWS. See High-performance work systems (HPWS)
HQ. See Headquarters (HQ)
HR. See Human resources (HR)
HRD. See Human resources director (HRD)
HRIS. See Human resource information systems (HRIS)
HRM approach. See Human Resource Management approach (HRM approach)
Human agency in social theory
, 271
Human resource information systems (HRIS)
, 2, 3, 11, 23, 35, 184
background
, 4–5
contributions
, 24–26
deployment
, 20
limitations
, 26
method
, 16
analyses
, 19
measures
, 17–19
participants
, 16–17
sample organization characteristics
, 17
previous HRIS adoption research
, 5–6
results
, 19
correlations among variables
, 21
hypotheses tests
, 19–22
regression analysis
, 22
SMEs
, 3
theories of information systems adoption
, 6–9
TOE model
, 9–16
Human Resource Management approach (HRM approach)
, 35, 62, 63, 174, 222, 288, 313–314
HRM4
, 212
HRM5
, 213
labels of HRM department
, 335
limitations of HRM practice monitor
, 330–334
Practice Monitor
, 317
practitioners
, 112
professional
activities of
, 334–335
primary role of
, 334–335
professionals
, 319–321, 323–325
research
, 262
secondary analysis
, 321, 325
bivariate correlations typification HRM department over time
, 328
data on ‘Personnel Administration’
, 326
e-HRM
, 328, 329
number of mentions, HRM practice monitor
, 330
statements on e-HRM, digital, computer
, 331
time spent by HRM professional
, 326
typification of HR department
, 327
Smart Industry research in
, 222, 244–245
direct effects on Job Characteristics
, 247–250
drastic organisational changes
, 222–223
employment debate
, 224–226
as inspiration for configurational approach
, 251–252
JCM
, 228–244
job characteristics
, 258–259
job design
, 226–227, 245–247
method
, 227
as moderator
, 250–251
Human resources (HR)
, 2, 35, 60, 116, 174, 176, 180, 183, 263
adopter/abandonment system dynamic model
, 81
analytics
, 60–61, 64, 80
Compliance Support
, 18
conceptualizing HR analytics as innovation
, 62–65
CORE’s role in making HR more strategic
, 192–193
department
, 102–103, 105
e-HRM technology
, 79–80
employee self-service
, 83
in FinCO
, 186
findings and discussion
, 40
benefits of innovative tools
, 49
criteria for classification of practices
, 45
digitalised HR system
, 47
digitisation model
, 46
innovation strategy
, 41
perception of digitalization
, 48
practices and systems
, 43
social media and mobile applications
, 42
‘super users’ of core system
, 50
T&D system
, 44
functions
, 95, 100, 203
HRM practice
, 62–63
as innovation
, 80–81
issues
, 212–214
literature review
, 35–39, 63–65
management fashions
, 82–83
methodology
, 39–40, 71
analysis
, 72–74
sample
, 71–72
metrics
, 60, 63–65
HR Analytics and
, 65
practices
, 146–147
professionals
, 191
skills
, 214
recommendations for HR practitioners
, 299–302
results
, 74–79
risks
, 297–298
service
, 190–191
theory and hypotheses
, 66
as innovation
, 66–68
as management fashion
, 68–69
management fashion theory
, 69–71
Human resources director (HRD)
, 148
Hypotheses tests/testing
, 19–22, 318
ICT
, 244, 313, 314
Ideation process
, 180
IDT. See Innovation diffusion theory (IDT)
IE. See Internal effectiveness (IE)
IHRIM. See International Human Resource Information Management (IHRIM)
ILO. See International Labour Organization (ILO)
Implementation costs
, 14, 18
Improved HR data
, 17
Individual-oriented models
, 8–9
“Industry 4.0”
, 222, 247, 248, 252
Informal recruitment processes
, 110–111
Information quality
, 11, 93, 99, 100
dimension
, 88
maximizing
, 101
Information systems (IS)
, 35, 89, 203
adoption theories
, 6
IDT
, 7–8
organizational-level adoption theories
, 8–9
TAM
, 6–7
TPB
, 7
UTAUT
, 8
issues in Australia
, 207–208
literatures
, 99, 104–105
managerial issues reported in IT literature
, 204–207
quality
, 97
sociomateriality in information systems research
, 267–272
success model
, 92–94
Information technology (IT)
, 34, 60, 138, 140, 174, 262
deployment
, 333
issues
, 206, 207
knowledgeable information technology staff
, 98
strategic alignment of
, 142–143
Informational e-HRM systems
, 89
Innovation
, 34
conceptualizing HR analytics as
, 63–65
diffusion
, 35, 51, 66, 79, 81
HR analytics as
, 66–68
innovation-decision process
, 67
Innovation diffusion theory (IDT)
, 7–8, 83
Innovativeness
, 118, 119, 120–121, 125, 128
Instagram
, 44, 118
Institutional theory
, 266
‘Institutionalists’ research
, 266
Integrative capabilities
, 141, 275
Intention to apply
, 124–125
for job
, 116, 130
job seekers
, 125
regression analysis of usability, attractiveness and interaction effects
, 127
Inter-level consequences
, 266
Inter-organisational service delivery
, 36
Internal effectiveness (IE)
, 206
International environments
, 176
International Human Resource Information Management (IHRIM)
, 61, 78–79
International Labour Organization (ILO)
, 289
Internet
, 36, 69, 264, 294
Internet of things (IoT)
, 37, 245, 252
Internet-based recruitment
, 115
Interviews
, 184, 209, 218
conducted
, 40
semi-structured
, 39, 211
transcribed
, 210
Intra-level consequences
, 266
Intra-organisational service delivery
, 36
Intranet
, 44, 45, 47, 204, 264, 315
IoT. See Internet of things (IoT)
Irish hotel industry
, 35
IS. See Information systems (IS)
IT. See Information technology (IT)
JCM. See Job characteristics model (JCM)
Job characteristics model (JCM)
, 227–228, 246, 258–259
and developments
, 228, 241
and findings regarding job character
, 228
identified job characteristics
, 241
graphical illustrations
, 241–244
direct effects of Smart Industry
, 247–250
Job design
, 223, 226–227
challenges
, 245
conceptual clarity
, 245–247
Smart Industry impact on
, 247
Job seekers
, 112–114, 125
perception of e-recruitment tools
, 131
perceptions and reactions
, 129
regression analysis of usability, attractiveness and interaction effects
, 127
willingness to apply
, 114
Knowledge processing system
, 97–98
Lean manufacturing approach
, 63
Legal guidelines
, 289–290
Line managers (LMs)
, 179, 183, 191–192
LinkedIn
, 43–44, 111, 117, 121–122, 124–125, 127–128
Linking code of conduct to training
, 299–300
LISREL
, 154, 158
Management fashion
HR analytics as
, 68–69
theory
, 62, 69–71, 79–80
Management innovation
, 63
Management system dimension
, 141
Manufacturing SMEs
, 138
alternative research model test
, 160–162
e-HRM
, 139
implications for theory and practice
, 162
return to strategic alignment model
, 164
SAM
, 163
SWOT approach
, 164–165
limitations
, 165–166
measurement model assessment
, 154
AVE
, 155
PLS
, 154
reliability, validity, and intercorrelations of research constructs
, 157
test of research model
, 156
methodology
data collection
, 148–151
operationalization of research concepts
, 144–148
research model
, 144, 145
research model assessment
, 158
covariance-based techniques
, 158
test of research model
, 159
variance
, 160
SHRM
, 140
taxonomic analysis of organizational capabilities
, 151
breakdown of antecedent, control, and SHRM performance variables
, 153
configurations
, 151
organizational capability configurations
, 152
use of e-HRM Software
, 154
theoretical and empirical background
, 140
e-HRM organizational capabilities
, 141–142
“Gestalts” alignment perspective
, 144
RBV theory
, 140–141
SHRM organizational capabilities
, 142
strategic alignment of IT
, 142–143
See also Small- to medium-sized enterprises (SME)
“Marker” variable
, 148
“Mass fashion”
, 70, 71
Measurement model assessment
, 154
AVE
, 155
PLS
, 154
reliability, validity, and intercorrelations of research constructs
, 157
test of research model
, 156
See also Research model—assessment
Measures
, 17–19, 120–121, 246
macro measures of system quality
, 100
objective SHRM performance
, 162
outcome
, 93
Microsoft Excel spreadsheet
, 96
MNCs. See Multinational corporations (MNCs)
Mobile applications
, 42, 203
“Moral courage”
, 289
Moral integrity, reliance on
, 290–291
Motivator-hygiene theory
, 226–227
Multi-level phenomenon
, 263, 264
Multidimensional framework of service innovation
, 36
Multinational corporations (MNCs)
, 174, 177
characteristics
, 176–183
consequences and impacts of e-HRM
, 189–190
CORE’s role in supporting business strategy
, 193
cost efficiency improvement
, 187
cost savings
, 190
global orientation improvement
, 187
HR service
, 190–191
HRM
, 174–175
impacts on different stakeholders
, 191
improving customer service and efficiency
, 187–188
LM
, 191–192
methods
, 183–185
motives
for e-HRM adoption
, 194
for introducing CORE
, 186
operational benefits and impacts of
, 194–195
practical implications
, 197
research limitations
, 196–197
stage for
, 175–176
stakeholders in MNC
, 193–194
strategic
e-HRM
, 175
HR role
, 188–189
impacts of e-HRM
, 195–196
potential of CORE
, 192–193
TM
, 192
Natural language processing techniques (NLP techniques)
, 63, 72, 80
Natural Language Toolkit (NLTK)
, 73
“Negativity bias”
, 293
Network-centric approach
, 244
Nexus of practices and material arrangements, e-HRM as
, 272
mangle of e-HRM
, 274–276
organisation of practice
, 273
NLP techniques. See Natural language processing techniques (NLP techniques)
NLTK. See Natural Language Toolkit (NLTK)
North American industrial products company
, 98–99
NVivo software package
, 210
Observability
, 35, 44, 50, 68, 75, 82
Online analytical processing tool (OLAP tool)
, 103–104
Online screening of candidates
, 294
Operational
goals
, 91–92, 203
objectives
, 265
perspective
, 88–89
Operationalization of research concepts
, 144
extant literature
, 146
firm’s e-HRM organizational capabilities
, 147
HR practices
, 146–147
HRM function
, 148
Oracle
, 61
HR analytics data sheet
, 61
PeopleSoft system
, 95
Organization(al)
, 102, 113, 298
attraction to organization as employer
, 120
capability configurations
, 152
breakdown of antecedent, control, and SHRM performance variables
, 153
use of e-HRM Software
, 154
context
, 12–14
culture
, 213
factors
, 9
growth
, 24
IT infrastructure capabilities
, 141
learning processes
, 277
organizational-level adoption theories
, 8–9
processes
, 277
protecting organizational reputation and brand
, 295–296
Participants
, 16–17, 118
“Partnership” approach
, 179
People & Strategy
, 75
Personnel Administration
, 318, 322, 326, 332, 333, 335
PLS
, 154, 158
Policies and processes, organizational perspective
, 102
Post-recruitment and selection concerns
, 295
HR risks
, 297–298
protecting organizational reputation and brand
, 295–296
social media competence
, 297
Practice theory
, 276
Pre-recruitment and selection issues
, 292
cyber-vetting or data mining applicants via social media
, 294–295
reputation management and employer branding
, 292–293
Predictive models
, 64
Project management
, 147, 186, 205, 278
Prospectors
, 146
Psychological empowerment
, 241
Radio frequency identification (RFID)
, 245
RBV. See Resource-based view (RBV)
Reactors
, 146
Realistic job previews
, 300
Recruitment process
, 110
Reductionism
, 266
Relational goals
, 91–92
Relational objectives
, 265
Relational ontology
, 271–272
Relative advantage
, 67–68
Reputation management
, 292–293, 300–301
Research model
, 144, 145
assessment
, 158
covariance-based techniques
, 158
test of research model
, 159
variance
, 160
See also Measurement model assessment
Research team
, 90
Resource-based view (RBV)
, 137, 140
theory
, 140–141
RFID. See Radio frequency identification (RFID)
SAM. See Strategic alignment model (SAM)
Scientific management
, 226
Service quality
, 93, 98, 100, 101
Shared performing
, 263–264
SHRM. See Society of Human Resource Management (SHRM); Strategic human resource management (SHRM)
Sierra-Cedar HR Systems Survey
, 72
Signalling theory
, 114, 129
SIM. See US Society for Information Management (SIM)
Six sigma approach
, 63
Small- to medium-sized enterprises (SMEs)
, 3, 4, 15, 138, 139, 158
implications for
, 25
SHRM performance of
, 166
taxonomic analysis of organizational capabilities of
, 151–154
vendor support
, 25–26
Smart Industry
, 222, 244–245
direct effects on Job Characteristics
, 247–250
as inspiration for configurational approach
, 251–252
job characteristics
, 258–259
as moderator
, 250–251
research in HRM field
, 222–223
drastic organisational changes
, 222–223
employment debate
, 224–226
JCM
, 228–244
job design
, 226–227, 245–247
method
, 227
“Smart”
industry as inspiration for configurational approach
, 251–252
smart-HRM
, 37
system
, 89
technologies
, 295
workforce management analytical systems
, 104
SMEs. See Small- to medium-sized enterprises (SMEs)
Snapchat
, 44
Social media
, 42, 110–112, 117
applications
, 43–44
browsing experience
, 129
impact of SNW features
, 113
legal and ethical guidelines
, 289–290
perceived SNW page attractiveness
, 120
perceived SNW page usability
, 120
post-recruitment and selection concerns
, 295–298
pre-recruitment and selection issues
, 292–295
recommendations for HR practitioners
, 299–302
reliance on moral integrity
, 290–291
time for critical reflection
, 302–303
Social media as recruitment tool
discussion
, 129
theoretical and managerial implications
, 129–130
job seekers
, 112–114
methodology
, 118
field survey
, 124–129
laboratory experiment
, 118–124
social networking websites
, 110–111
theoretical Framework
, 114–118
Social science theory
, 267
Social system
, 66
Social theory
, 269
Society of Human Resource Management (SHRM)
, 299
Sociomaterial phenomena
, 267
Sociomateriality in information systems research
, 267
emphasising role of human agency
, 268
ERP system
, 268–269
sociomateriality and agency
, 270–272
Software vendors
, 18
Sophisticated analytics
, 65
Spatial-temporal manifolds of human activity
, 276
S-shaped model
, 66
Standards
, 102
Strategic alignment model (SAM)
, 163
return to
, 164
Strategic e-HRM in MNC
, 175
characteristics
, 176
consequences and impact of e-HRM
, 178–179
motives for adopting
, 176–178
strategic potential of e-HRM
, 179–181
theoretical framework of study and summary of literature review
, 181–183
consequences and impacts of e-HRM
, 189
improving transparency
, 189–190
standardization and higher level of control
, 189
CORE’s role in supporting business strategy
, 193
cost efficiency improvement
, 187
cost savings
, 190
global orientation improvement
, 187
HR service
, 190–191
impacts on different stakeholders
, 191
improving customer service and efficiency
, 187–188
LM
, 191–192
methods
, 183
background information of case company
, 185
research approach, design, and methods
, 183–185
motives for e-HRM adoption
, 194
motives for introducing CORE
, 186
operational benefits and impacts of
, 194–195
practical implications
, 197
research limitations
, 196–197
stage for
, 175–176
stakeholders in MNC
, 193–194
strategic HR role
, 188–189
strategic impacts of e-HRM
, 195–196
strategic potential of CORE
, 192–193
TM
, 192
Strategic HR role
, 188–189
Strategic human resource management (SHRM)
, 138, 140
breakdown of antecedent, control, and SHRM performance variables
, 153
descriptive statistics
, 150
organizational capabilities
, 142
See also Electronic human resource management (e-HRM)
“Strengths-weaknesses-opportunities-threats” approach (SWOT approach)
, 164–165
Structural equation modeling
, 154
Structuration theory
, 264, 268, 270
SWOT approach. See “Strengths-weaknesses-opportunities-threats” approach (SWOT approach)
System dynamic model of innovation diffusion
, 81
System quality
, 93, 94, 97–98
recommendations
, 103–104
T&D. See Training and development (T&D)
TA. See Technology application (TA)
“Talent analytics”
, 64, 65
TAM. See Technology acceptance model (TAM)
Taxonomic analysis of organizational capabilities of SMEs
, 151
breakdown of antecedent, control, and SHRM performance variables
, 153
configurations
, 151
organizational capability configurations
, 152
use of e-HRM software
, 154, 155
Taxonomic statistical techniques
, 143
Technical system dimension
, 141
Technological determinism
, 269
Technology
, 102, 211
context
, 10–12
technological factors
, 8, 9, 11
technology-mediated networks
, 264
Technology acceptance model (TAM)
, 6–7, 91
Technology adoption model. See Technology acceptance model (TAM)
Technology application (TA)
, 206
Technology infrastructure (TI)
, 206
Technology Proponent
, 323
Technology–organization–environment model (TOE model)
, 9
environmental context
, 14–16
framework
, 10
organization context
, 12–14
technology context
, 10–12
Theory of planned behavior (TPB)
, 7, 91
TI. See Technology infrastructure (TI)
Time, HR analytics
, 66
Time for critical reflection
, 302–303
TM. See Top management (TM)
TOE model. See Technology–organization–environment model (TOE model)
Tokenization
, 72
Top management (TM)
, 183, 192
Top Management Support
, 18, 24
TPB. See Theory of planned behavior (TPB)
Training and development (T&D)
, 37
Transcribed interviews
, 210
Transformational
goals
, 92
objectives
, 265
perspective
, 88, 89
Transparency
, 189–190
Triability
, 68
Triangulation
, 166, 183
Twitter
, 38–39, 43–44, 111
Unified theory of acceptance and use of technology (UTAUT)
, 8, 91
Upward spiral
, 224
US Small Business Administration
, 16
US Society for Information Management (SIM)
, 205
Variance
, 160
Vault
, 293
Virtual HRM
, 263
Voluntarism in
, 268, 269
Web 1.0
, 36–37, 45
domain
, 117–118
recruitment methods
, 115
Web 2.0
, 36–37, 45, 116–117
e-recruitment
, 130
on recruiters
, 116–117
Web 3.0
, 36, 37, 45
Web-based
HRM
, 263–264
services
, 36
technology
, 138
Wireless communication
, 245
Workforce Analytics
, 64n1, 72, 79, 89
Workforce management
analyses
, 103
data quality in
, 102–103
decision-making analysis
, 101
“smart” system for
, 89, 98–99
tools
, 88
YouTube
, 43–45
- Prelims
- Chapter 1 An Investigation of the Factors Driving the Adoption of Cloud-Based Human Resource Information Systems by Small- and Medium-Sized Businesses
- Chapter 2 Assessing the Degree of Human Resource Innovation: An Exploratory Analysis of Irish Hotel Corporations
- Chapter 3 HR Analytics: Here to Stay or Short Lived Management Fashion?
- Chapter 4 e-HRM Systems in Support of “Smart” Workforce Management: An Exploratory Case Study of System Success
- Chapter 5 Professional and Non-Professional Social Media as Recruitment Tools: The Impact on Job Seekers’ Attraction and Intention to Apply
- Chapter 6 Aligning the e-HRM and Strategic HRM Capabilities of Manufacturing SMEs: A “Gestalts” Perspective
- Chapter 7 Aiming for Strategic e-HRM: Motives and Consequences of e-HRM Implementation in an MNC
- Chapter 8 e-HRM Challenges: An Australian Perspective
- Chapter 9 Smart Industry Research in the Field of HRM: Resetting Job Design as an Example of Upcoming Challenges
- Chapter 10 What about Agency in e-HRM Research?
- Chapter 11 Changing Role of Social Media at Work: Implications for Recruitment and Selection
- Chapter 12 The dis-app-earance of HRM: Impact of Digitization on the HRM Profession
- Index